2021
Uptake of evidence by physicians: De-adoption of erythropoiesis-stimulating agents after the TREAT trial
Vu K, Zhou J, Everhart A, Desai N, Herrin J, Jena AB, Ross JS, Shah ND, Karaca-Mandic P. Uptake of evidence by physicians: De-adoption of erythropoiesis-stimulating agents after the TREAT trial. BMC Nephrology 2021, 22: 284. PMID: 34419007, PMCID: PMC8379779, DOI: 10.1186/s12882-021-02491-y.Peer-Reviewed Original ResearchConceptsErythropoiesis-stimulating agentsChronic kidney diseaseEpoetin alfaDarbepoetin alfaTREAT trialTypes of ESAsNew clinical evidencePrimary care physiciansMedicare AdvantageUptake of evidenceCare physiciansAnemia treatmentClinical evidenceKidney diseasePhysician genderMedicare feeUnsafe treatmentSegmented regression approachStudy periodPhysiciansService populationConsistent changesAlfaHigher useTreatment
2020
Timely estimation of National Admission, readmission, and observation-stay rates in medicare patients with acute myocardial infarction, heart failure, or pneumonia using near real-time claims data
Li SX, Wang Y, Lama SD, Schwartz J, Herrin J, Mei H, Lin Z, Bernheim SM, Spivack S, Krumholz HM, Suter LG. Timely estimation of National Admission, readmission, and observation-stay rates in medicare patients with acute myocardial infarction, heart failure, or pneumonia using near real-time claims data. BMC Health Services Research 2020, 20: 733. PMID: 32778098, PMCID: PMC7416804, DOI: 10.1186/s12913-020-05611-w.Peer-Reviewed Original ResearchQuality of informed consent documents among US. hospitals: a cross-sectional study
Spatz ES, Bao H, Herrin J, Desai V, Ramanan S, Lines L, Dendy R, Bernheim SM, Krumholz HM, Lin Z, Suter LG. Quality of informed consent documents among US. hospitals: a cross-sectional study. BMJ Open 2020, 10: e033299. PMID: 32434934, PMCID: PMC7247389, DOI: 10.1136/bmjopen-2019-033299.Peer-Reviewed Original ResearchConceptsInformed consent documentsHOSPITAL scoreUS hospitalsMean hospital scoresRetrospective observational studyConsent documentsCross-sectional studyEight-item instrumentService patientsElective proceduresProcedure typeObservational studySurgical proceduresMedicare feeHospitalHospital qualityMeasure scoresInformed consentMost hospitalsSpearman correlationScoresFace validityIndependent ratersOutcomesStakeholder feedbackPatient and provider-level factors associated with changes in utilization of treatments in response to evidence on ineffectiveness or harm
Smith LB, Desai NR, Dowd B, Everhart A, Herrin J, Higuera L, Jeffery MM, Jena AB, Ross JS, Shah ND, Karaca-Mandic P. Patient and provider-level factors associated with changes in utilization of treatments in response to evidence on ineffectiveness or harm. International Journal Of Health Economics And Management 2020, 20: 299-317. PMID: 32350680, PMCID: PMC7725279, DOI: 10.1007/s10754-020-09282-2.Peer-Reviewed Original ResearchConceptsPermanent atrial fibrillationType 2 diabetesAtrial fibrillationPermanent atrial fibrillation patientsProvider-level factorsAtrial fibrillation patientsEffective new therapiesPrimary care providersUse of medicationsProvider-level characteristicsUtilization of treatmentHigh-quality health careDronedarone useInterrupted time-series regression modelsFibrillation patientsMedication useDiabetes patientsProvider characteristicsCare providersMedicare feeNew therapiesService claimsFemale providersPatientsMedications
2019
Risk of Readmission After Discharge From Skilled Nursing Facilities Following Heart Failure Hospitalization: A Retrospective Cohort Study
Weerahandi H, Li L, Bao H, Herrin J, Dharmarajan K, Ross JS, Kim KL, Jones S, Horwitz LI. Risk of Readmission After Discharge From Skilled Nursing Facilities Following Heart Failure Hospitalization: A Retrospective Cohort Study. Journal Of The American Medical Directors Association 2019, 20: 432-437. PMID: 30954133, PMCID: PMC6486375, DOI: 10.1016/j.jamda.2019.01.135.Peer-Reviewed Original ResearchConceptsSkilled nursing facilitiesSNF dischargeRetrospective cohort studySNF lengthHeart failureHF hospitalizationComposite outcomeCohort studyNursing facilitiesService beneficiaries 65Heart failure hospitalizationRisk of readmissionHazard rate ratiosFailure hospitalizationUnplanned readmissionHF diagnosisHospital dischargePostdischarge outcomesSNF stayMedicare patientsMedicare feeHome transitionPatientsReadmissionDay 3
2018
Association of the Overall Well-being of a Population With Health Care Spending for People 65 Years of Age or Older
Riley C, Roy B, Herrin J, Spatz ES, Arora A, Kell KP, Rula EY, Krumholz HM. Association of the Overall Well-being of a Population With Health Care Spending for People 65 Years of Age or Older. JAMA Network Open 2018, 1: e182136. PMID: 30646154, PMCID: PMC6324481, DOI: 10.1001/jamanetworkopen.2018.2136.Peer-Reviewed Original ResearchConceptsMedicare FFS beneficiariesPeople 65 yearsHealth care spendingFFS beneficiariesCare spendingPopulation-based cross-sectional studyLower health care spendingHealth care system capacityCross-sectional studyHealth care systemPopulation levelPayment modelsCare payment modelsHighest quintileInverse associationStudy interventionMAIN OUTCOMEMedicare feeMedicare beneficiariesUS national studyOverall healthMedian household incomeBeing IndexCare systemDemographic characteristics
2016
Association Between Hospital Penalty Status Under the Hospital Readmission Reduction Program and Readmission Rates for Target and Nontarget Conditions
Desai NR, Ross JS, Kwon JY, Herrin J, Dharmarajan K, Bernheim SM, Krumholz HM, Horwitz LI. Association Between Hospital Penalty Status Under the Hospital Readmission Reduction Program and Readmission Rates for Target and Nontarget Conditions. JAMA 2016, 316: 2647-2656. PMID: 28027367, PMCID: PMC5599851, DOI: 10.1001/jama.2016.18533.Peer-Reviewed Original ResearchConceptsHospital Readmissions Reduction ProgramAcute myocardial infarctionReadmission ratesReadmissions Reduction ProgramHeart failurePenalty statusNontarget conditionsMedicare feeMean readmission rateThirty-day riskRetrospective cohort studyUnplanned readmission rateReduction programsHRRP announcementHRRP implementationPenalized hospitalsCohort studyService patientsMyocardial infarctionMAIN OUTCOMEExcess readmissionsMedicare beneficiariesService beneficiariesHospitalPatientsDevelopment and validation of a simple risk score to predict 30‐day readmission after percutaneous coronary intervention in a cohort of medicare patients
Minges KE, Herrin J, Fiorilli PN, Curtis JP. Development and validation of a simple risk score to predict 30‐day readmission after percutaneous coronary intervention in a cohort of medicare patients. Catheterization And Cardiovascular Interventions 2016, 89: 955-963. PMID: 27515069, PMCID: PMC5397364, DOI: 10.1002/ccd.26701.Peer-Reviewed Original ResearchMeSH KeywordsAgedAged, 80 and overAlgorithmsDecision Support TechniquesFemaleHumansLogistic ModelsMaleMedicareMultivariate AnalysisOdds RatioPatient ReadmissionPercutaneous Coronary InterventionPredictive Value of TestsRegistriesReproducibility of ResultsRisk AssessmentRisk FactorsTime FactorsTreatment OutcomeUnited StatesConceptsRisk of readmissionPCI patientsRisk scoreMultivariable logistic regression modelRisk score developmentDays of dischargeSimple risk scoreTime of dischargeModel c-statisticLogistic regression modelsStepwise selection modelCathPCI RegistryHospital dischargeReadmission ratesClinical factorsRevascularization proceduresValidation cohortC-statisticReadmissionHigh riskMedicare feeLower riskService claimsPatientsCohort
2015
Association of hospital volume with readmission rates: a retrospective cross-sectional study
Horwitz LI, Lin Z, Herrin J, Bernheim S, Drye EE, Krumholz HM, Hines HJ, Ross JS. Association of hospital volume with readmission rates: a retrospective cross-sectional study. The BMJ 2015, 350: h447. PMID: 25665806, PMCID: PMC4353286, DOI: 10.1136/bmj.h447.Peer-Reviewed Original ResearchConceptsReadmission ratesHospital volumeRetrospective cross-sectional studyUS acute care hospitalsHospital readmission ratesAcute care hospitalsCross-sectional studyMedical cancer treatmentCare hospitalAdult dischargesHospital characteristicsMedicare feeCancer treatmentHospitalAssociationDaysService dataPatientsCardiovascularGynecologyQuintileNeurology
2014
Development and use of an administrative claims measure for profiling hospital-wide performance on 30-day unplanned readmission.
Horwitz LI, Partovian C, Lin Z, Grady JN, Herrin J, Conover M, Montague J, Dillaway C, Bartczak K, Suter LG, Ross JS, Bernheim SM, Krumholz HM, Drye EE. Development and use of an administrative claims measure for profiling hospital-wide performance on 30-day unplanned readmission. Annals Of Internal Medicine 2014, 161: s66-75. PMID: 25402406, PMCID: PMC4235629, DOI: 10.7326/m13-3000.Peer-Reviewed Original ResearchConceptsUnplanned readmissionReadmission measuresReadmission ratesReadmission riskMedicare feeHospital-wide readmission measureRisk-standardized readmission ratesPayer dataAdministrative Claims MeasureRisk-standardized ratesAverage-risk patientsUnplanned readmission rateDays of dischargeHospital risk-standardized readmission ratesAdult hospitalizationsComorbid conditionsPrincipal diagnosisClaims dataService claimsService beneficiariesReadmissionMeasure development studiesMedicaid ServicesRisk adjustmentHospital
2011
Quality of Care in the US Territories
Nunez-Smith M, Bradley EH, Herrin J, Santana C, Curry LA, Normand SL, Krumholz HM. Quality of Care in the US Territories. JAMA Internal Medicine 2011, 171: 1528-1540. PMID: 21709184, PMCID: PMC3251926, DOI: 10.1001/archinternmed.2011.284.Peer-Reviewed Original ResearchConceptsAcute myocardial infarctionRisk-standardized readmission ratesRisk-standardized mortality ratesHeart failureMortality rateReadmission ratesProcess measuresHospital characteristicsHighest risk-standardized mortality ratesPrincipal discharge diagnosisQuality of careHealth care qualityDischarge diagnosisService patientsMyocardial infarctionTerritorial HospitalNonfederal hospitalsUS territoriesMedicare feePneumoniaHospitalCare qualityPatientsPerformance of hospitalsUS states